from pydantic import BaseModel, Field


class IndustrialAVMRequest(BaseModel):
    """Request schema for industrial property rent estimation."""

    province: str = Field(..., min_length=1, description="Province name (e.g. Bình Dương)")
    region: str = Field(
        ..., min_length=1, description="Region: south, north, central, mekong_delta"
    )
    park_occupancy_rate: float = Field(
        ..., ge=0, le=1, description="Industrial park occupancy rate (0-1)"
    )
    park_area_ha: float = Field(..., gt=0, description="Total park area in hectares")
    park_age_years: int = Field(..., ge=0, description="Industrial park age in years")
    distance_to_port_km: float = Field(
        ..., ge=0, description="Distance to nearest seaport in km"
    )
    distance_to_airport_km: float = Field(
        ..., ge=0, description="Distance to nearest airport in km"
    )
    distance_to_highway_km: float = Field(
        ..., ge=0, description="Distance to nearest highway in km"
    )
    property_type: str = Field(
        ...,
        description="Industrial property type: warehouse, factory, ready_built_factory, "
        "ready_built_warehouse, open_yard, office_in_park",
    )
    area_m2: float = Field(..., gt=0, description="Leasable area in m²")
    ceiling_height_m: float = Field(
        0.0, ge=0, description="Ceiling/clear height in meters"
    )
    floor_load_ton_m2: float = Field(
        0.0, ge=0, description="Floor load capacity in tons/m²"
    )
    power_capacity_kva: float = Field(
        0.0, ge=0, description="Allocated power capacity in kVA"
    )
    industry_demand_index: float = Field(
        0.5, ge=0, le=1, description="Local industry demand index (0-1)"
    )
    fdi_province_musd: float = Field(
        0.0, ge=0, description="Province FDI inflow in million USD (trailing 12 months)"
    )
    labor_cost_province_vnd: float = Field(
        0.0, ge=0, description="Average province labor cost in VND/month"
    )
    logistics_connectivity_score: float = Field(
        0.5, ge=0, le=1, description="Logistics connectivity score (0-1)"
    )


class IndustrialComparable(BaseModel):
    """A comparable industrial property used for the estimation."""

    park_name: str
    province: str
    property_type: str
    area_m2: float
    rent_usd_m2: float
    similarity_score: float = Field(..., ge=0, le=1)


class FeatureImportance(BaseModel):
    """Feature importance from the model prediction."""

    feature: str
    importance: float = Field(..., ge=0, le=1)


class IndustrialAVMResponse(BaseModel):
    """Response schema for industrial property rent estimation."""

    estimated_rent_usd_m2: float = Field(
        ..., description="Estimated monthly rent in USD per m²"
    )
    confidence: float = Field(
        ..., ge=0, le=1, description="Prediction confidence score"
    )
    rent_range_low_usd_m2: float = Field(
        ..., description="Lower bound rent estimate in USD/m²"
    )
    rent_range_high_usd_m2: float = Field(
        ..., description="Upper bound rent estimate in USD/m²"
    )
    annual_rent_usd_m2: float = Field(
        ..., description="Estimated annual rent in USD/m²"
    )
    total_monthly_rent_usd: float = Field(
        ..., description="Total monthly rent for the requested area in USD"
    )
    comparables: list[IndustrialComparable] = Field(
        default_factory=list, description="Similar industrial properties for reference"
    )
    drivers: list[FeatureImportance] = Field(
        default_factory=list,
        description="Top feature drivers for this prediction",
    )
    model_version: str = Field("heuristic-v1", description="Model version used")